PubMed · 7421572
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P A Kolers, S R Palef, L B Stelmach. 1980. Graphemic analysis underlying literacy.. https://doi.org/10.3758/bf03198271
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Objects can be recognized independently of the view they present, of their position on the retina, or their scale. It has been suggested that one basic mechanism that makes this possible is a memory effect, or a trace, that allows associations to be made between consecutive views of one object. In this work, we explore the possibility that this memory trace is provided by the sustained activity of neurons in layers of the visual pathway produced by an extensive recurrent connectivity. We describe a model that contains this high recurrent connectivity and synaptic efficacies built with contributions from associations between pairs of views that is simple enough to be treated analytically. The main result is that there is a change of behavior as the strength of the association between views of the same object, relative to the association within each view of an object, increases. When its value is small, sustained activity in the network is produced by the views themselves. As it increases above a threshold value, the network always reaches a particular state (which represents the object) independent of the particular view that was seen as a stimulus. In this regime, the network can still store an extensive number of objects, each defined by a finite (although it can be large) number of views.
Contour detection may be mediated by lateral interactions between neighboring cortical neurons whose receptive fields have collinear axes of preferred orientation. This hypothesis was tested in psychophysical experiments and computer simulations using a contour detection task in which observers searched for groups of Gabor patches that followed spatially extended contour paths embedded in noise consisting of several hundred Gabor patches with random positions and orientations. The orientation-selective units in the simulated neural network were linked by facilitatory interconnections whose strength depended on the geometry (distance, curvature, change in curvature) of smooth curves connecting the orientation axes of units in a pairwise fashion. Psychophysical detection performance was much higher for contour signal groups that followed closed rather than open-ended paths. However, just two sudden changes in orientation of neighboring Gabor patch elements in closed-path contours reduced detection performance to the same levels obtained with open-ended contours. These psychophysical data agreed with the results of the neural network simulations. Furthermore, the simulations also accounted for previous findings that removal of a single Gabor patch element from a closed-path contour group significantly degraded detection performance. We conclude that closure alone is not sufficient to enhance the visibility of a contour. However, if a closed contour meets certain geometric constraints, then lateral interactions based on these constraints can generate facilitation that reverberates around the closed path, thereby enhancing the contour's visibility.
The sequence of images generated by motion between observer and object specifies a spatiotemporal signature for that object. Evidence is presented that such spatiotemporal signatures are used in object recognition. Subjects learned novel, three-dimensional, rotating objects from image sequences in a continuous recognition task. During learning, the temporal order of images of a given object was constant. During testing, the order of images in each sequence was reversed, relative to its order during learning. This image sequence reversal produced significant reaction time increases and recognition rate decreases. Results are interpreted in terms of object-specific spatiotemporal signatures.